Role Description

Understanding business objectives and build models that help achieving the desired results
Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
Verifying data quality, and/or ensuring it via data cleaning
Defining validation strategies, pre-processing or feature engineering to be done on a given dataset
Training models and tuning their hyperparameters
Analyzing the errors of the model and designing strategies to overcome them
Independently handle technical and architectural discussions with internal and external stakeholders
Collaborate with the team and communicate effectively, to solve problems
Establish benchmarks, standards, techniques and mechanisms for defining, measuring, and optimizing non-functional requirements.
Provide technical thought leadership and improvise the processes being followed
Mentoring and managing team members, by giving constant feedback, and by providing guidance

Key Desirables

6+ years of experience in building AI/ML based solutions
Proficiency with Python, Scala, R and basic libraries for machine learning such as scikit-learn and pandas
Strong experience in Deep Learning and Machine Learning frameworks (NLP / CNN / RNN - TensorFlow / Keras )
Strong experience in Data Science, Statistics and probability, Data Engineering and Exploratory data analysis
Good understanding on Image Classification and Text Classification Algorithms.
Ability to write robust and testable code
Able to write and deploy code on cloud and knowledge of Docker.
Strong experience in cloud platforms and services for training and deploying the models
A Degree / Nanodegree / Certification in (AI/ML specialization)